Error correction techniques are used in a number of communication and storage systems. Error correction codes, such as Reed-Solomon codes, add one or more redundant bits to a digital stream prior to transmission or storage, so that a decoder can detect and possibly correct errors caused by noise or other interference. One class of error correction codes are referred to as “turbo” codes. Generally, turbo codes employ a combination of two or more systematic convolutional or block codes. Typically, an iterative decoding technique is employed where the output of each decoding step, for example, from an inner receiver, serves as an input to the subsequent decoding step performed by an outer receiver. In many implementations, the inner receiver generates log-likelihood ratios (LLRs) that are processed by the outer receiver.
In a CDMA receiver, for example, an inner receiver typically demodulates the received signal into symbols and the outer receiver forms, processes and decodes each frame, comprised of a collection of symbols. The output signal of the inner receiver is often quantized to a smaller number of bits and then processed by a soft input/soft output decoder. U.S. patent application Ser. No. 10/387,876, entitled “Method and Apparatus for Decoder Input Scaling Based on Interference Estimation in CDMA,” for example, discloses a technique for scaling the decoder input for a CDMA receiver to a smaller number of bits to reduce the memory requirement. In order to maintain the decoder performance for a smaller number of input bits, the disclosed method estimates the interference of the inner receiver output and scales the decoder input such that its variance is maintained.
A number of techniques have been proposed or suggested for adjusting various parameters of a turbo decoder to improve the throughput or Bit Error Rate (BER) performance. Y. Wu and B. Woerner, “The Influence of Quantization and Fixed Point Arithmetic Upon the BER Performance of Turbo Codes,” Proc. IEEE Veh. Tech. Conf., Houston, Tex. (May, 1999), for example, evaluates the influence of quantization and fixed point arithmetic upon the BER performance of turbo decoders. Wu and Woerner demonstrate that with proper scaling of the received signal prior to quantization, there is no degradation of the BER performance with eight bit quantization (or even four bit quantization).
Generally, the inner receiver in such conventional turbo decoding techniques generates floating point LLRs (soft bits) that are scaled in a linear manner, and then mapped to a fixed point. Most known techniques for scaling decoder inputs have used a gain control method. For example, the mean square or mean absolute values of the inner receiver output have been employed. The technique disclosed in the above-referenced U.S. patent application Ser. No. 10/387,876 employ a noise variance of the channel in order to scale the decoder input. A need exists for methods and apparatus for scaling or shaping the LLR distribution in a manner that improves the BER performance. A further need exists for methods and apparatus for scaling or shaping the LLR distribution in a non-linear manner.